A wide variety of medical devices have been developed to monitor patient conditions and possibly deliver therapy to the patient. In some cases, the medical devices comprise external medical devices that are used to monitor a patient. In other cases, the medical devices are implantable medical devices (IMDs) that are surgically implanted inside a patient for short or long term therapy. Telemetry can be used to communicate sensed electrograms from one medical device to another medical device, e.g., from an IMD to an external medical device.
One common example of an IMD is a pacemaker. A pacemaker typically includes one or more pacing and sensing leads for delivery of pacing pulses to a patient's heart. Another example of an IMD is a combination pacemaker-cardioverter-defibrillator. Other examples include implantable brain stimulators, implantable gastric system stimulators, implantable nerve stimulators or muscle stimulators, implantable lower colon stimulators, implantable drug or beneficial agent dispensers or pumps, implantable cardiac signal loops or other types of recorders or monitors, implantable gene therapy delivery devices, implantable incontinence prevention or monitoring devices, implantable insulin pumps or monitoring devices, and so on.
Medical devices, including IMDs and external medical devices, often sense and record electrograms of a patient. Electrograms refer to signals which represent recorded changes in electric potential of the patient. Examples of electrograms include electrocardiograms, i.e., recorded electrical potentials associated with a patient's heart; and electroencephalograms, i.e., recorded electrical potentials associated with a patient's brain. Other more specific examples of electrograms include atrial electrograms, coronary sinus (CS) electrograms, esophageal electrograms, high right atrial (HRA) electrograms, His bundle electrograms, intra-atrial electrograms, intracardiac electrograms, right ventricular electrograms, right ventricular apical electrograms, sinus node electrograms, and the like.
Signal processing of electrograms is a common challenge in the medical field. In particular, it is often necessary to identify specific features of an electrogram so that medical events can be identified in the patient, such as arrhythmias in the patients heart. However, in many cases, signal noise can complicate analysis of electrograms. For this reason, denoising techniques are desirable in order to reduce or eliminate noise from electrograms.